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How the Manufacturing Sector Can Use Data Analytics to Grow Business

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Big data has immense potential in almost every industry including the manufacturing sector. Any organization that can collect and organize useful data to answer various questions about their functioning can benefit from big data and data analytics. Paper documents can be scanned and converted into electronic formats using document scanning services to improve data access and ensure smooth workflow.

Manufacturing Sector

In the present Extreme Data Economy, data has become more important than ever before. In 2011, the World Economic Forum recognized personal data as an asset for corporations. Angela Merkel, chancellor one of the world’s largest manufacturing economies, has said that data will be the raw material of the 21st century. Data provides an opportunity for social economic growth and helps you understand your customers, gain valuable insights and make better business decisions.

Effective Data Analytics and Use – Real Life Examples

In the manufacturing industry, operations can be improved faster and more efficiently with data analytics. The process of analytics provides you with more focused and actionable insights that are so important to continuously tweak your production line.

  • Honeywell Process Solutions KRC Research study found that 67 percent of manufacturing executives are investing in Big Data analytics in order to reduce cost. They are making investment in data integration and management as well to gain a competitive edge. The study also found that big data analytics can reduce breakdowns by up to 26 percent and cut unscheduled downtime by nearly a quarter.
  • Tire manufacturer Continental is revamping their business model to be known as a technology company first rather than premium tire manufacturer or an automotive supplier. Continental has built remote monitoring technology into their tire to quickly collect data. This new technology has transformed the fleet maintenance from a laborious process to an automated, proactive and targeted process. Their transition to a data-powered company helps them thrive and capitalize on extreme data in a way that makes business sense for them.
  • Manufacturer Toyota recently completed a reorganization, focused on expanding data science technology. They developed a program called Toyota Connected by consolidating Toyota initiatives across data analytics, data center management and data driven services. It provides offerings like connected and autonomous cars to know the taste and preferences of customers.
    Toyota and Continental are examples of industries harnessing the power of data to revolutionize their business. These companies are getting ahead of the learning curve and overcoming the challenges and gradually transforming their data. With data increasing in importance and with the implementation of GDPR, the roles of chief data officers, data scientists and data protection officers have become ever more significant. Data powered businesses operate at high speed and scale with higher complexities and a new era of extreme data management is evolving that needs more data-driven roles.

IDC estimates the global volume of digital data will rise 40 times in 2020, and as data increases, it becomes more unpredictable, complex and perishable. The need for real time insights derived from data is important to become a true data-powered business.

Global Big Data Analytics in Manufacturing Industry Market: 2018 to 2023

The global big data analytics in the manufacturing industry market is expected to grow at a CAGR of 38.63 percent during the forecast period 2018 to 2023. It is estimated that the data generated today in the current global scenarios is equal to data generated over the last decade. With the concept of Industry 4.0 (current trend of automation and data exchange in manufacturing technologies), the amount of data generated in manufacturing sector is expected to increase. The manufacturing sector has to monitor various variables to ensure the quality of the end product.

Advantages Offered by Data Analytics

Big data analytics can help reduce processing flaws, increase efficiency, improve quality of the products, and save time as well as money. Analytics helps in:

  • Supply planning
  • Tracking product quality and defects
  • Tracking defects in manufacturing processes
  • Obtaining supplier performance data for contract negotiations
  • Supplier, components, and parts defect tracking
  • Forecasting output
  • Testing and simulation of new processes
  • Increasing energy efficiency
  • Custom product design
  • Better quality assurance
  • Managing supply chain risks

Data processing services provided by a good data entry company can ensure clean and actionable data that can be analyzed to gather valuable insights. With the right data, and by incorporating strong analysis and visualization tools, the manufacturing sector can obtain a more detailed understanding of how their production line operates and how it can be streamlined further for business success.

About Rajeev R

Rajeev R

Manages the day-to-day operations of MOS from NY. With an interest in information technology, Rajeev has guided MOS to extensive use of digital technology and the internet that benefits MOS as well as MOS clients.